The present invention relates to a semiconductor device suitable for constructing a neural network.
A neuro chip, in which an electronic circuit or a neural network substituted for neurons, which are elements constituting a neural network represented by a cerebrum and the function of the synapse, which is a coupling element between neurons in/outputting signals in/from the neurons, is realized on a semiconductor chip, is discussed e.g. in "Nikkei Micro Device (in Japanese)", July 1988, pp. 53-65.
The synapse, which is an important constituting element in a neuro chip as described above, is constructed e.g. by a variable conductance circuit and a neuron is composed of an operational amplifying circuit.
Heretofore, in order to realize a variable conductance circuit, MOSFETs have been used. For example, as indicated in FIG. 1a, it is possible to vary the channel conductance by varying the amount of electric charge stored in the gate 7 of a MOSFET 8. Further, as indicated in FIG. 1b, the conductance can be varied by connecting a number of FETs in parallel and by varying the number of FETs, which are in the on-state.
However, the method indicated in FIG. 1a has a problem from the point of view of the precision, the reproducibility and the reliability of the conductance, because the amount of the stored electric charge varies in the course of time because of the existence of leak current. On the other hand the method indicated in FIG. 1b has a problem that the number of FETs connected in parallel is too great and as the result the density cannot be increased, when it is intended to integrate them.
It is also tried to realize a neural network by using optical techniques and a synapse, in which a spacial light modulator, a hologram or an emulsion mask is used, is reported, ibid. pp. 66-71. Further, as an optical bistable element, whose transmission coefficient for input light varies in 2 levels, a semiconductor element, in which a double barrier resonant tunneling diode is combined with a p-n junction diode having a multiple quantum well structure, as described in "Technical Research Report of the Electronic Information Communication Society (in Japanese)" Vol. 88, No. 6, pp. 63-67 (1988).
It is expected that wiring, which would be complicated, if it were fabricated in the form of an electronic circuit, can be simplified by using light.
In the prior art neuro system, a neural network system using a special light modulator tube as a synapse stores a signal light pattern in the form of a pattern of electric charge formed on a surface of an LiNbO.sub.3 crystal and the stored information is read out by using a laser light beam. Further in a system using a hologram as a synapse an LiNbO.sub.3 crystal is used as the hologram material and the interference fringe of the signal light with the reference light is memorized. For these reasons, in these systems, it can be relatively easily effected to rewrite the stored information, which is inevitable for the learning function. However, since the construction of these systems is of large scale and complicated, it is difficult to try to integrate them.
On the other hand, in a system, in which an emulsion mask is used as the synapse, it is possible to form it on one chip by dividing the emulsion mask into a number of regions in a matrix form and by storing the transmission coefficient of each of the regions while varying it with weight of .+-.0, .+-.1, .+-.2. However, the information, which has been once written in the mask, is fixed and since it cannot be rewritten, it has no learning function.
On the other hand, in the optical bistable element, in which a double barrier resonant tunneling diode is combined with a p-n junction diode having a multiple quantum well structure, the transmission coefficient for the input light can be varied only in two levels and therefore the multiple-valued logic signal processing, which is inevitable for a neuron system, is impossible.